logo

3D Visualization of Swings



1. Approach : Sift through the data by checking NaNs, getting summary statistics, and since this is a time series data, plot time series trends. From the time series trends, I noticed some ups and downs in variables like bat speed, hand speed, etc. which can be attributed to noise while collecting the data. I used a low-pass butterworth filter having a cutoff of 25Hz for the metrics in the time series plots and 10 Hz for barrel & knob tracking data.
After that I focused on dividing the visuals into two parts with the swing views from three different perspectives and time series plots of the metrics. I also added a 3D figure to properly visualize the swing path.

2. Observation : Considering similar pitch conditions for both the players, I came up with the following observations.

Player 1

Player 1 has a gradual downward swing that transitions into a steep upward motion, indicating a focus on producing lift, with relatively controlled body rotation and an elevated vertical bat angle to maximize fly ball potential. Their extended bat path post-contact, though slightly slower in achieving the same level of bat speed, is characterized by a controlled swing. This could result into swings with higher launch angles and better adjustability to pitches in different locations.


Player 2

Player 2 shows an aggressive swing that levels off near contact with a compact follow-through (from 3D Viz), achieving higher bat speed but also a flattened bat path, indicating a more explosive swing focused on power with potentially a line-drive approach. This aggressive approach might help with high exit velocity, but it might also result into ground outs due to the bat path.


3. Extension :

Swing views

Bird’s Eye View

Side View

Catcher View